The graph represents a network of 4,730 Twitter users whose tweets in the requested range contained "#CDC", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 08 April 2020 at 09:23 UTC.
The requested start date was Wednesday, 08 April 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 1-day, 21-hour, 52-minute period from Monday, 06 April 2020 at 02:07 UTC to Wednesday, 08 April 2020 at 00:00 UTC.
Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".
The graph is directed.
The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.
The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Author Description
Vertices : 4730
Unique Edges : 4987
Edges With Duplicates : 1443
Total Edges : 6430
Number of Edge Types : 4
Tweet : 1857
MentionsInRetweet : 3165
Replies to : 520
Mentions : 888
Self-Loops : 1857
Reciprocated Vertex Pair Ratio : 0.00969461948618517
Reciprocated Edge Ratio : 0.0192030724915987
Connected Components : 1349
Single-Vertex Connected Components : 805
Maximum Vertices in a Connected Component : 1419
Maximum Edges in a Connected Component : 2325
Maximum Geodesic Distance (Diameter) : 18
Average Geodesic Distance : 6.075335
Graph Density : 0.000186246796228748
Modularity : 0.709684
NodeXL Version : 1.0.1.429
Data Import : The graph represents a network of 4,730 Twitter users whose tweets in the requested range contained "#CDC", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 08 April 2020 at 09:23 UTC.
The requested start date was Wednesday, 08 April 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 1-day, 21-hour, 52-minute period from Monday, 06 April 2020 at 02:07 UTC to Wednesday, 08 April 2020 at 00:00 UTC.
Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".
Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : GraphServerTwitterSearch
Graph Term : #CDC
Groups : The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.
Edge Color : Edge Weight
Edge Width : Edge Weight
Edge Alpha : Edge Weight
Vertex Radius : Betweenness Centrality
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[347] covid,19 [158] 内閣官房に私がチーム長の,#新型コロナウイルス感染症対策 [158] #新型コロナウイルス感染症対策,テックチーム [158] テックチーム,anti [158] anti,covid [158] 19,tech [158] tech,team [158] team,#actt [158] #actt,を立ち上げ [158] を立ち上げ,it企業など12社のオンライン参加を得て開催 Top Word Pairs in Tweet in G1:
[72] covid,19 [45] cloth,face [42] #covid19,#coronavirus [28] #cdc,#coronavirus [28] face,coverings [27] #cdc,recommends [26] #who,#cdc [24] #coronavirus,#coronaviruspandemic [23] face,mask [23] face,masks Top Word Pairs in Tweet in G2:
[46] realdonaldtrump,#cdc [31] cause,death [29] hospitals,list [28] wth,realdonaldtrump [28] #cdc,tells [28] tells,hospitals [28] list,#covid [28] #covid,cause [28] death,assuming [27] outrageous,top Top Word Pairs in Tweet in G3:
[158] 内閣官房に私がチーム長の,#新型コロナウイルス感染症対策 [158] #新型コロナウイルス感染症対策,テックチーム [158] テックチーム,anti [158] anti,covid [158] covid,19 [158] 19,tech [158] tech,team [158] team,#actt [158] #actt,を立ち上げ [158] を立ち上げ,it企業など12社のオンライン参加を得て開催 Top Word Pairs in Tweet in G4:
[21] #boletindominicano,#covid19 [18] #covid19,#wuhancoronavirus [11] #coronavirus,#boletindominicano [9] daily,cdcgov [9] cdcgov,update [8] cdcgov,#cdc [8] #pssresources,legalbeagle1215 [8] #covid19,#coronavirus [7] wear,mask [7] cdcgov,cdcdirector Top Word Pairs in Tweet in G5:
[97] lying,ass [97] ass,cdc [97] cdc,creating [97] creating,fear [97] fear,manipulating [97] manipulating,numbers [97] numbers,#lookitup [97] #lookitup,#yarimakaramaapp [97] #yarimakaramaapp,#warriormode [97] #warriormode,#cdc Top Word Pairs in Tweet in G6:
[90] corporate,news [90] news,reports [90] reports,rising [90] rising,death [90] death,tolls [90] tolls,#highwire [90] #highwire,reveals [90] reveals,#cdc [90] #cdc,marching [90] marching,orders Top Word Pairs in Tweet in G7:
[52] cause,#autism [34] dr,sears [34] sears,md [34] md,co [34] co,host [34] host,thedoctors [34] thedoctors,reading [34] reading,full [34] full,#cdc [34] #cdc,2004 Top Word Pairs in Tweet in G8:
[50] bannon,need [50] need,see [50] see,government's [50] government's,model [50] model,need [50] need,#cdc [50] #cdc,nih [50] nih,dr [50] dr,birx's [50] birx's,deckplate Top Word Pairs in Tweet in G9:
[63] didn,think [63] think,less [63] less,respect [63] respect,doctors [63] doctors,longer [63] longer,goes [63] goes,deafening [63] deafening,silence [63] silence,99 [62] kevin_tuttle76,didn Top Word Pairs in Tweet in G10:
[72] #faucifraud,#nih [72] #nih,#cdc [72] #cdc,media [72] media,working [72] working,hard [72] hard,keep [72] keep,#lockdown [72] #lockdown,#shutdown [72] #shutdown,going [72] going,hiding Top Replied-To in Entire Graph:
Top Replied-To in G2:
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Top Replied-To in G9:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G10: